import numpy as np
import holoviews as hv
hv.extension('bokeh', 'matplotlib')

data = np.load('../assets/twophoton.npz')
calcium_array = data['Calcium']
calcium_array.shape

ds = hv.Dataset((np.arange(50), np.arange(111), np.arange(62), calcium_array),
                ['Time', 'x', 'y'], 'Fluorescence')
ds

type(ds.data), list(ds.data.keys())

ds.clone(datatype=['xarray']).data

%opts Image (cmap='viridis')
ds.to(hv.Image, ['x', 'y']).hist()

ROIs = data['ROIs']
roi_bounds = hv.Path([hv.Bounds(tuple(roi)) for roi in ROIs])
print(ROIs.shape)

%%opts Image [width=400 height=400 xaxis=None yaxis=None] 
%%opts Path (color='white') Text (text_color='white' text_font_size='8pt')

opts = dict(halign='left', valign='bottom')
roi_text = hv.NdOverlay({i: hv.Text(roi[0], roi[1], str(i), **opts) for i, roi in enumerate(ROIs)})
(ds[21].to(hv.Image, ['x', 'y']) * roi_bounds * roi_text).relabel('Time: 21')

x0, y0, x1, y1 = ROIs[60]
roi = ds.select(x=(x0, x1), y=(y0, y1), time=(250, 280)).relabel('ROI #60')
roi.to(hv.Image, ['x', 'y'])

%%opts GridSpace [shared_xaxis=True shared_yaxis=True]
roi.to(hv.Curve, 'Time').grid()

%%opts Overlay [show_legend=False width=600]
agg = roi.aggregate('Time', np.mean, spreadfn=np.std)
hv.Spread(agg) * hv.Curve(agg)